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001476494 001__ 1476494
001476494 003__ OCoLC
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001476494 020__ $$a9789819958443$$q(electronic bk.)
001476494 020__ $$a981995844X$$q(electronic bk.)
001476494 0247_ $$a10.1007/978-981-99-5844-3$$2doi
001476494 035__ $$aSP(OCoLC)1396062738
001476494 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE
001476494 049__ $$aISEA
001476494 050_4 $$aQA76.87
001476494 08204 $$a006.32$$223/eng/20230912
001476494 1112_ $$aNCAA (Conference)$$n(4th :$$d2023 :$$cHefei Shi, China ; Online)
001476494 24510 $$aInternational Conference on Neural Computing for Advanced Applications :$$b4th International Conference, NCAA 2023, Hefei, China, July 7-9, 2023, Proceedings.$$nPart I /$$cHaijun Zhang, Yinggen Ke, Zhou Wu, Tianyong Hao, Zhao Zhang, Weizhi Meng, Yuanyuan Mu, editors.
001476494 2463_ $$aNCAA 2023
001476494 260__ $$aSingapore :$$bSpringer,$$c2023.
001476494 300__ $$a1 online resource (595 p.).
001476494 4901_ $$aCommunications in Computer and Information Science ;$$vv.1869
001476494 500__ $$a4.3 Results
001476494 500__ $$aIncludes author index.
001476494 5050_ $$aIntro -- Preface -- Organization -- Contents - Part I -- Contents - Part II -- Neural Network (NN) Theory, NN-Based Control Systems, Neuro-System Integration and Engineering Applications -- ESN-Based Control of Bending Pneumatic Muscle with Asymmetric and Rate-Dependent Hysteresis -- 1 Introduction -- 2 The FSBPM -- 2.1 Structure of the FSBPM -- 2.2 The Asymmetric Rate-Dependent Hysteresis of the FSBPM -- 2.3 Mathematical Description of the FSBPM -- 3 Feedback Control Strategy Combined with the Feedforward Compensation -- 3.1 Inversion of the Hysteresis Based on ESN
001476494 5058_ $$a3.2 Feedback Control Strategy Based on Feedforward Compensation -- 4 Experiments -- 4.1 Experimental Platform -- 4.2 Feedback Control Experiments -- 5 Conclusions -- References -- Image Reconstruction and Recognition of Optical Flow Based on Local Feature Extraction Mechanism of Visual Cortex -- 1 Introduction -- 2 Methods -- 2.1 MT Optical Flow Stimulation -- 2.2 Image Reconstruction Using NMF Algorithm -- 2.3 Image Reconstruction Using the SNN Model -- 3 Results -- 4 Conclusion -- 4.1 Summary -- 4.2 Outlook -- References
001476494 5058_ $$aConditional Diffusion Model-Based Data Augmentation for Alzheimer's Prediction -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Diffusion Probabilistic Model -- 2.3 Conditional DDPM -- 3 Experiments -- 3.1 Dataset and Experiment Design -- 3.2 Evaluation of Generated Data -- 3.3 Evaluation with Compared Methods -- 4 Conclusion -- References -- Design of Dissolved Oxygen Online Controller Based on Adaptive Dynamic Programming Theory -- 1 Introduction -- 2 Preliminary Knowledge -- 2.1 Optimal Problem Formulation -- 2.2 Online ESN-ADP Algorithm -- 2.3 FRRLS Algorithm for Training ESN-ADP
001476494 5058_ $$a3 Convergence of ESN-Based Value Function Approximation -- 3.1 Convergence of ESN-Based Value Function Approximation -- 4 Experiment and Discussion -- 5 Conclusion -- References -- Ascent Guidance for Airbreathing Hypersonic Vehicle Based on Deep Neural Network and Pseudo-spectral Method -- 1 Introduction -- 2 Dynamic Modeling -- 3 Guidance Law Design -- 3.1 Offline Trajectory Database Establishment -- 3.2 DNN Structure and Training -- 3.3 The Sequential Calling Strategy and the Overall Scheme -- 4 Numerical Simulations -- 4.1 The Database Establishment -- 4.2 Real-Time Performance
001476494 5058_ $$a4.3 Comparison of Different Numbers of the DNNs -- 5 Conclusion -- References -- Machine Learning and Deep Learning for Data Mining and Data-Driven Applications -- Image Intelligence-Assisted Time-Series Analysis Method for Identifying "Dispersed, Disordered, and Polluting" Sites Based on Power Consumption Data -- 1 Introduction -- 2 Preliminary -- 2.1 Clustering Algorithm -- 2.2 Gramian Angular Field -- 3 Algorithm Procedure -- 3.1 H-K-means -- 3.2 Imaging Time Series -- 3.3 Mutual Information -- 3.4 Perceptual Hash Algorithm -- 4 Practical Validation -- 4.1 Background -- 4.2 Implementation
001476494 506__ $$aAccess limited to authorized users.
001476494 520__ $$aThe two-volume set CCIS 1869 and 1870 constitutes the refereed proceedings of the 4th International Conference on Neural Computing for Advanced Applications, NCAA 2023, held in Hefei, China, in July 2023. The 83 full papers and 1 short paper presented in these proceedings were carefully reviewed and selected from 211 submissions. The papers have been organized in the following topical sections: Neural network (NN) theory, NN-based control systems, neuro-system integration and engineering applications; Machine learning and deep learning for data mining and data-driven applications; Computational intelligence, nature-inspired optimizers, and their engineering applications; Deep learning-driven pattern recognition, computer vision and its industrial applications; Natural language processing, knowledge graphs, recommender systems, and their applications; Neural computing-based fault diagnosis and forecasting, prognostic management, and cyber-physical system security; Sequence learning for spreading dynamics, forecasting, and intelligent techniques against epidemic spreading (2); Applications of Data Mining, Machine Learning and Neural Computing in Language Studies; Computational intelligent Fault Diagnosis and Fault-Tolerant Control, and Their Engineering Applications; and Other Neural computing-related topics.
001476494 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed September 12, 2023).
001476494 650_0 $$aNeural computers$$vCongresses.
001476494 655_0 $$aElectronic books.
001476494 7001_ $$aZhang, Haijun$$c(Professor of computer science)
001476494 7001_ $$aKe, Yinggen.
001476494 7001_ $$aWu, Zhou$$c(Researcher on optimization and artificial intelligence)
001476494 7001_ $$aHao, Tianyong.
001476494 7001_ $$aZhang, Zhao$$c(Computer scientist)
001476494 7001_ $$aMeng, Weizhi.
001476494 7001_ $$aMu, Yuanyuan.
001476494 77608 $$iPrint version:$$aZhang, Haijun$$tInternational Conference on Neural Computing for Advanced Applications$$dSingapore : Springer,c2023$$z9789819958436
001476494 830_0 $$aCommunications in computer and information science ;$$v1869.
001476494 852__ $$bebk
001476494 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-99-5844-3$$zOnline Access$$91397441.1
001476494 909CO $$ooai:library.usi.edu:1476494$$pGLOBAL_SET
001476494 980__ $$aBIB
001476494 980__ $$aEBOOK
001476494 982__ $$aEbook
001476494 983__ $$aOnline
001476494 994__ $$a92$$bISE